the dark side of operational wi fi calling services
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The Dark Side of Operational Wi-Fi Calling Services Tian Xie 1 , Guan-Hua Tu 1 , Chi-Yu Li 2 , Chunyi Peng, Mi Zhang 1 1 Michigan State University 2 National Chiao Tung University 3 Purdue University Wi-Fi Calling Services Wi-Fi Calling


  1. The Dark Side of Operational Wi-Fi Calling Services Tian Xie 1 , Guan-Hua Tu 1 , Chi-Yu Li 2 , Chunyi Peng, Mi Zhang 1 1 Michigan State University 2 National Chiao Tung University 3 Purdue University

  2. Wi-Fi Calling Services • Wi-Fi Calling services empower mobile users to access voice and text services over Wi-Fi instead of cellular networks. • All of four U.S. major operators have launched Wi-Fi calling services since 2016 – Verizon, AT&T, T-Mobile, and Sprint. • By 2020, Wi-Fi calling services will take 53% of mobile IP voice service usage including VoLTE (26%) and others (21%).

  3. Wi-Fi Calling Services Primer • Specifically, they are SIP-based voice and text services, however, they are using a 3GPP-modified version. • Developed on top of 3GPP IMS (IP Multimedia Subsystem) • Operators use IMS to provide users with IP-based services such as VoIP • It uses the same infrastructure for VoLTE (Voice over LTE) users. • Radio Access Network (RAN) • Wi-Fi Access Point (Wi-Fi Calling) • eNodeB (VoLTE) • LTE Core Network (CN) • ePDG (Evolved Packet Data Gateway, Wi-Fi calling) • PDN-GW (Public Data Network Gateway) • AAA (Authentication, Authorization, and Accounting) • IMS (IP Multimedia Subsystem)

  4. Wi-Fi Calling Security Mechanisms • Using well-examined 3GPP Authentication and Key Agreement (AKA) and SIM-based security adopted by VoLTE – symmetric cryptography. • All Wi-Fi calling signaling and voice/text packets are delivered through IPsec (Internet Protocol Security) – ciphering and integrity protection. How Does It Go Wrong?

  5. Finding 1: Wi-Fi calling devices ces will activate Wi-Fi calling services over an insecu ecure Wi-Fi network

  6. Vulnerability: Wi-Fi calling devices do not exclude insecure Wi-Fi networks – (design defect of standards) • Vulnerability – Wi-Fi calling standards don’t exclude insecure Wi-Fi • Two Wi-Fi access point selection modes do not consider security factors yet!! • Manual (use a prioritized list) • Automated (ANDSF, Access network discovery and selection function) • Validation: • Deploy an insecure Wi-Fi network using a Wi-Fi router which is vulnerable to ARP spoofing attack – foundation of a variety of MITM attacks • I.e., victim’s WIFI packets will be intercepted and delivered to adversaries • We test whether the Wi-Fi calling devices keep connecting to the above Wi-Fi router All tested Wi-Fi calling devices connected to the insecure Wi-Fi router!!!

  7. Finding 2: Wi-Fi calling devices ces do not employ security defense against the common Wi-Fi ARP spoofing attacks

  8. Vulnerability: Wi-Fi calling devices do not defend against ARP spoofing attacks –(implementation issue of devices) • Vulnerability -Wi-Fi calling devices always accept ARP Reply message • All packets sent by Wi-Fi calling devices can be redirected to adversaries • Validation • We use EtterCap to send ARP reply message to Wi-Fi calling devices. Adversaries can capture all Wi-Fi packets sent by the victim

  9. Finding 3: Wi-Fi calling devices ces and infrastructure indeed deploy extra security mechanisms for malicious Wi-Fi attacks, however, i , it t is not ot en enough.

  10. A system-switch mechanism for Wi-Fi Calling Service DoS Attacks • With the aforementioned two findings, adversaries can launch Wi-Fi Calling service DoS attacks • Discarding all intercepted Wi-Fi signaling and voice/text packets • System-switch (Wi-Fi-> Cellular) • If an user fails to dial a Wi-Fi voice call, the mobile device will switch to use cellular- network-based voice services. • If Wi-Fi calling service operators cannot route an incoming call to users by Wi-Fi calling , the operators will switch it to use cellular-network-based one. For users, they are free of voice/text DoS attacks.

  11. Vulnerability: Service continuity is not revised accordingly – (design defect of standards) • Service continuity can seamlessly switch an ongoing Wi-Fi calling call to back to cellular-network-based voice call • However, it is only triggered while the quality of Wi-Fi radio signals is bad What if Wi-Fi radio quality is good but Wi-Fi calling service quality is poor? • We start dropping all Wi-Fi calling packets after the call conversation is started (Wi-Fi radio quality is good) The system-switch security mechanism is bypassed!! No cellular-based voice call is initiated.

  12. Finding 4: Wi Wi-Fi callin ing s ser ervic vice op operators do not take extra security mechanisms to protect the encr crypted Wi-Fi calling packets

  13. Vulnerability : The Wi-Fi calling traffic is vulnerable to side-channel attacks – (operational slip of operator) • Vulnerability -Wi-Fi calling is the only service that is carried by the IPSec channel between the mobile device and ePDG. • Adversaries may infer various Wi-Fi calling events such as dialing calls, receiving calls, etc. • Validation • Apply C4.5 to analyze IPSec traffic patterns • We are able to infer six Wi-Fi calling events • Evt I: Activating Wi-Fi calling service • Evt II: Receiving an incoming call • Evt III: Dialing an outgoing call • Evt IV: Sending a text • Evt V: Receiving a text • Evt VI: Deactivating Wi-Fi calling service

  14. Two Proof-of-concept Attacks

  15. Attack 1: User privacy leakage • The call statistics has been proven effective to infer user privacy including personality[1], mood[2], malicious behaviors[3], etc . • Devising WiCA (Wi-Fi Calling Analyzer) to infer a Wi-Fi calling user’s call statistics • Who initiates the call (an incoming call or an outgoing call) • Who hangs up the call first (caller or callee) • Ringing time (how long the callee answers the call) • Call conversation time [1] Y.-A. de Montjoye, J. Quoidbach, F. Robic, and A. S. Pentland, “Predicting personality using novel mobile phone-based metrics,” in International conference on social computing, behavioral-cultural modeling, and prediction. Springer, 2013 [2] S. Thomee, A. H ´ arenstam, and M. Hagberg, “Mobile phone use and ¨ stress, sleep disturbances, and symptoms of depression among young adults-a prospective cohort study,” BMC public health, vol. 11, no. 1, p. 66, 2011. [3] V. Balasubramaniyan, M. Ahamad, and H. Park, “Callrank: Combating SPIT using call duration, social networks and global reputation,” in CEAS’07, 2007

  16. Infer call statistics@WiCA • WiCA’s finite state machine • Record the number of Uplink and Downlink packets transmitted every 2 seconds • Classify them into three categories by packet size: • Small (<200 bytes), Medium (200-800 bytes), Large (>800 bytes) • Our observations on small packets

  17. Ringing time inference • We observe that Wi-Fi calling service servers will keep sending small packets to both of caller and callee after SIP RINGING message is sent by the callee. No uplink small packets after callee’s phone is ringed Small downlink packets can be used to detect Ringing Packets sent by the callee Packets sent by Wi-Fi calling server Packet arrivals for the event ‘receiving a call with a ringtone’ (callee perspective).

  18. Conversation time inference • We observe small packets on the uplink and downlink during the call conversation Packets sent by the callee Packets sent by Wi-Fi calling server Packet arrivals for ‘Talking’ (callee perspective).

  19. Call initiation and termination inference • Relying on the directions and patterns of large packets • E.g., if the ringing or talking event is detected and the first large packet (SIP INVITE) is sent by the monitored Wi-Fi user => It is an outgoing call • E.g., if the talking and not-talking events are detected and the last large packet (200 OK) is sent by the Wi-Fi server => the monitored Wi-Fi user terminates call first

  20. Performance of WiCA • Who initiates, Who ends call first : 100% accurate • Ringing time and conversation time • Maximum error is less than 0.8 seconds.

  21. Another application of WiCA • By face recognition, It is not difficult to identify who you are Peng Mi Xie Tu Li • How about their IP addresses if they are using free public WiFi?

  22. WiCA with visual recognition system • With the mature visual recognition system, WiCA’s call statistics can help to identify both of user identities and their IP addresses • The ways people are surfing and talking on phones are different We know which of IP addresses is to initiate Wi-Fi calling call and its call statistics.

  23. Attack 2: Telephony harassment or denial of voice service attack (THDoS) • We devise a telephony harassment or denial of voice service attack against Wi-Fi calling users. • It can bypass the security defenses deployed on Wi-Fi calling devices and the infrastructure. • The attack is based on the manipulation of the delivery of Wi-Fi calling signaling and voice packets for an ongoing call. • It contains several variants.

  24. Results of Discarding Wi-Fi Signaling and Voice packets Wi-Fi calling Call Flow

  25. Four Call Attack Variants • Attack Wi-Fi signalings • Annoying-Incoming-Call Attack • Victim is callee: • He/she keeps receiving incoming calls • By discarding 180 Ringing message or 183 Session Progress message • Zombie-Call Attack – a call cannot be ended • Victim is caller: • The callee has answered the incoming call. • However, the caller’s device gets stuck in the dialing screen and will keep hearing the alerting tone. • The conversation is never started. • By discarding 200 OK message

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